OpenMT: Open Source Machine Translation Using Hybrid Methods
نویسندگان
چکیده
The main goal of the OpenMT project is the development of open source machine translation architectures based on hybrid models and advanced syntactic–semantic processors. These architectures combine the three main Machine Translation (MT) frameworks, Rule-based (RBMT), Statistical (SMT) and Example–based (EBMT), into hybrid systems. Defined architectures and results will be open source, allow for a rapid development and adaptation of new advanced machine translation systems for other languages. The project deals with four different languages: English, Spanish, Catalan and Basque. The translation systems developed for all language pairs will be internally evaluated using a rich set of linguistic metrics, and in different international evaluation campaigns.
منابع مشابه
Wikipedia and Machine Translation: killing two birds with one stone
In this paper we present the free/open-source language resources for machine translation created in OpenMT-2 wikiproject, a collaboration framework that was tested with editors of Basque Wikipedia. Post-editing of Computer Science articles has been used to improve the output of a Spanish to Basque MT system called Matxin. For the collaboration between editors and researchers, we selected a set ...
متن کاملEgyptian Arabic to English Statistical Machine Translation System for NIST OpenMT'2015
The paper describes the Egyptian Arabicto-English statistical machine translation (SMT) system that the QCRI-ColumbiaNYUAD (QCN) group submitted to the NIST OpenMT’2015 competition. The competition focused on informal dialectal Arabic, as used in SMS, chat, and speech. Thus, our efforts focused on processing and standardizing Arabic, e.g., using tools such as 3arrib and MADAMIRA. We further tra...
متن کاملRefining Word Segmentation Using a Manually Aligned Corpus for Statistical Machine Translation
Languages that have no explicit word delimiters often have to be segmented for statistical machine translation (SMT). This is commonly performed by automated segmenters trained on manually annotated corpora. However, the word segmentation (WS) schemes of these annotated corpora are handcrafted for general usage, and may not be suitable for SMT. An analysis was performed to test this hypothesis ...
متن کاملA Hybrid Machine Translation System Based on a Monotone Decoder
In this paper, a hybrid Machine Translation (MT) system is proposed by combining the result of a rule-based machine translation (RBMT) system with a statistical approach. The RBMT uses a set of linguistic rules for translation, which leads to better translation results in terms of word ordering and syntactic structure. On the other hand, SMT works better in lexical choice. Therefore, in our sys...
متن کاملMulti-Engine Machine Translation with an Open-Source Decoder for Statistical Machine Translation
We describe an architecture that allows to combine statistical machine translation (SMT) with rule-based machine translation (RBMT) in a multi-engine setup. We use a variant of standard SMT technology to align translations from one or more RBMT systems with the source text. We incorporate phrases extracted from these alignments into the phrase table of the SMT system and use the open-source dec...
متن کامل